Alignment of single-cell trajectories to compare cellular expression dynamics

Ayelet Alpert, Lindsay S. Moore, Tania Dubovik, Shai S. Shen-Orr

Research output: Contribution to journalArticlepeer-review


Single-cell RNA sequencing and high-dimensional cytometry can be used to generate detailed trajectories of dynamic biological processes such as differentiation or development. Here we present cellAlign, a quantitative framework for comparing expression dynamics within and between single-cell trajectories. By applying cellAlign to mouse and human embryonic developmental trajectories, we systematically delineate differences in the temporal regulation of gene expression programs that would otherwise be masked.

Original languageEnglish
Pages (from-to)267-270
Number of pages4
JournalNature Methods
Issue number4
StatePublished - 3 Apr 2018

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Cell Biology


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